|Publication number||US7554485 B2|
|Application number||US 11/664,025|
|Publication date||Jun 30, 2009|
|Filing date||Jul 7, 2005|
|Priority date||Sep 28, 2004|
|Also published as||DE102004046873A1, EP1797450A1, EP1797450B1, US20080106459, WO2006034886A1|
|Publication number||11664025, 664025, PCT/2005/53244, PCT/EP/2005/053244, PCT/EP/2005/53244, PCT/EP/5/053244, PCT/EP/5/53244, PCT/EP2005/053244, PCT/EP2005/53244, PCT/EP2005053244, PCT/EP200553244, PCT/EP5/053244, PCT/EP5/53244, PCT/EP5053244, PCT/EP553244, US 7554485 B2, US 7554485B2, US-B2-7554485, US7554485 B2, US7554485B2|
|Original Assignee||Robert Bosch Gmbh|
|Export Citation||BiBTeX, EndNote, RefMan|
|Patent Citations (18), Non-Patent Citations (1), Referenced by (7), Classifications (20), Legal Events (5)|
|External Links: USPTO, USPTO Assignment, Espacenet|
The present invention relates to a radar sensor and an associated method for distance and cruise control of a motor vehicle by which objects in front of the vehicle in the direction of travel are detected and at least the distance, relative velocity, and azimuth angle variables of the recognized objects with respect to the vehicle are ascertained, the change over time of the reflection point of the radar beam on the object being ascertained and a classification of the detected object being ascertained as a function of the change over time of the reflection point.
A radar sensor for adaptive distance and cruise control is described in the publication “adaptive Fahrgeschwindigkeitsregelung ACC” [Adaptive cruise control ACC] published by Robert Bosch GmbH, April 2002 (ISBN-3-7782-2034-9). The radar sensor emits radar beams and receives partial beams reflected back by objects within the sensor coverage area and carries out a cruise control in the sense of controlling a constant distance as a function of the measured relative velocity and the distance of objects ahead and, in the absence of objects ahead, carries out a cruise control in the sense of controlling a constant velocity.
A disadvantage of radar sensors for distance and cruise control is that the reflection points of the detected objects which reflect back the emitted radar beam are variable, depending on the angle of observation, and thus the reflection points of the objects ahead may migrate constantly on the object. This results in a measurement inaccuracy which is superimposed on the measured variables of distance d, azimuth angle φ of the object with respect to the main axis of the sensor, and relative speed vrel as measuring errors which are manifested in a statistical noise of these measured variables.
In accordance with example embodiments of the present invention, a device and a method by which the disadvantages of the related art are overcome by ascertaining the measuring errors for distance d, relative velocity vrel, and azimuth angle φ so that more precise object tracking is implementable and an object classification may be performed on the basis of the size and the change over time of the reflection migrations and/or the number of reflection points per detected object, this object classification advantageously also being usable again for a more precise prediction of object position.
In accordance with an example embodiment, the spatial extent of the change of the reflection point is advantageously detected over a predetermined period of time. This makes it possible to infer the size of the object on the basis of object migrations that are variable over time and also makes it possible to perform an object classification in which the objects that are recognized are classified with regard to size.
In addition, it may be advantageous if the spatial extent is ascertained on the basis of changes over time in the azimuth angle of the reflection point. It may also be advantageous if the number of reflection points on the object is also analyzed for classification of the object. Thus, objects in the form of trucks will have a larger number of reflection points because they have a larger reflective surface and in most cases also have a more fractured surface than passenger vehicles, so there may be more reflection points than in the case of passenger vehicles.
It may also be advantageous if the instantaneous position of the recognized objects is calculated in advance from a previously ascertained object position and a previously ascertained relative velocity of the object and the spatial change of the reflection point is ascertained from the deviation in the instantaneous object position and the one calculated in advance. If reflection migration occurs during the previously ascertained object reflection and the instantaneous object reflection, i.e., if the reflection point on the object changes, the result is a movement in addition to the variable object position, this movement being measurable due to the migration of the reflection. By ascertaining the deviation between this object position calculated in advance and the ascertained reflection position, it is possible to ascertain the spatial extent of the reflection migration if both reflection points belong to the same object. Since in the case of reflection migration, the measured relative velocity hardly undergoes any change and the reflection point is able to jump to the object surface only within a certain range, object migrations and multiple object reflections may be assigned to this one object, and it is possible to infer the size of the object detected ahead by analyzing the migration of the reflection.
It may also be advantageous if the objects are assigned to one of the object classes as part of the object classification, i.e., passenger vehicles, trucks, two-wheeled vehicles, manhole covers, or other objects. From ascertainment of the extent of the object, it is possible to assign the recognized objects to one of the aforementioned object classes, so that an advance calculation of future object positions may be performed with higher precision because objects of the two-wheeled vehicle object class, for example, may have greater transverse speeds than objects assigned to the truck object class, for example.
It may also be advantageous if objects which have already been assigned to an object class are assigned to a different object class in a subsequent measuring cycle because a measured reflection migration on the object allows the inference that the object reflection surface is larger than would be possible according to the previously assigned object class. It is thus appropriate to transfer objects classified as two-wheeled vehicle objects to the object class of passenger vehicles or to transfer objects previously classified as passenger vehicles to the object class of trucks. A change in object class in the opposite direction, the object class being altered in the sense that it characterizes objects having smaller reflective surfaces and/or a change in object class from truck to passenger vehicle or from passenger vehicle to two-wheeled vehicle, is not appropriate because objects of an object class for which a large reflective surface has already been ascertained such as trucks would not necessarily result in a large reflection migration at a later measurement time.
It may also be advantageous if the deviation between the instantaneous object position and the one calculated in advance is Kalman filtered.
In addition, it may be advantageous if the Kalman-filtered deviation and/or the ascertained object class is used for a more accurate advance calculation of the future position of the object recognized from the instantaneously ascertained object position and the instantaneously ascertained relative velocity of the object.
Implementation of the method according to the present invention in the form of a control element provided for a control unit of an adaptive cruise control of a vehicle is of particular importance. A program that is capable of running on a computer, in particular on a microprocessor or signal processor, and is suitable for execution of the method according to the present invention, is stored in the control element. Thus, in this case, the present invention is implemented by a program stored in the control element so that this control element equipped with the program represents the present invention in the same way as does the method which is suitably executed by the program. An electric memory medium, e.g., a read-only memory, may be used in particular as the control element.
Other features, possible applications, and advantages of the present invention may be derived from the following description of exemplary embodiments of the present invention which are depicted in the figures. All the features described or depicted here either alone or in any combination constitute the object of the present invention, regardless of how they are combined.
Exemplary embodiments of the present invention are explained in greater detail below on the basis of figures.
An advance calculation of the object position for point in time tn+2 was calculated on the basis of relative velocity vrel and distance d plus azimuth angle φ at point in time tn+1 and this object position at point in time tn+2 which was calculated in advance is compared with the actually measured object position of reflection point 12, making it possible to ascertain the deviation between these two values. Since radar reflection point 12 has migrated by distance Δdn+2 on the object between point in time tn+1 and point in time tn+2, the deviation between the object position calculated in advance and the actually ascertained object position is much greater for point in time tn+2 because the reflection migration by distance Δdn+2 has additionally been added. The time correlation in the deviation of the instantaneously measured object position and the one calculated in advance is analyzed in particular. Reflection migration is characterized by a large time-correlated error between these two values. This is manifested as if a low-frequency signal were superimposed on the measured values. Generally, a measuring noise is not correlated, so that reflection migration is detectable by a correlation analysis and the existing measuring noise does not affect the object classification. Thus the large time-correlated error is recognizable via the correlation of the instantaneously measured object position with the one calculated in advance and may then be used for object classification.
By ascertaining this object migration distance, it is also possible to infer the size of the object because larger reflection migrations are possible on a truck, labeled with reference number 11 in
After step 19, the method begins again at step 13 and repeats.
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|U.S. Classification||342/90, 342/70, 342/94|
|International Classification||G01S7/41, G01S13/66, G01S13/93|
|Cooperative Classification||G01S2013/9346, G01S2013/9325, G01S2013/9321, G01S2013/935, G01S13/931, G01S7/411, G01S17/936, G01S17/58, G01S13/58, G01S7/4802, G01S2013/9353|
|European Classification||G01S13/93C, G01S13/58, G01S7/41A|
|Mar 27, 2007||AS||Assignment|
Owner name: ROBERT BOSCH GMBH, GERMANY
Free format text: ASSIGNMENT OF ASSIGNORS INTEREST;ASSIGNOR:JORDAN, JUEDIGER;REEL/FRAME:019142/0614
Effective date: 20070122
|Dec 24, 2012||FPAY||Fee payment|
Year of fee payment: 4
|Feb 10, 2017||REMI||Maintenance fee reminder mailed|
|Jun 30, 2017||LAPS||Lapse for failure to pay maintenance fees|
|Aug 22, 2017||FP||Expired due to failure to pay maintenance fee|
Effective date: 20170630